Method for detecting ineligibility of a beneficiary and system

ABSTRACT

A method and system are presented for identifying improper benefit payments to an ineligible beneficiary. Record data may be accessed from a financial institution and may be analyzed to identify patterns within the banking transactions. Deviations may be identified between a pre-benefit pattern and a post-benefit pattern by applying one or more rules, which may be ranked. The deviations that are identified may be determined to be either in compliance, in noncompliance, or within some acceptable level of compliance. A level of noncompliance outside of a range of acceptable noncompliance may result in generating a request for an action to be taken, such as an audit of the beneficiary. The aforementioned methods may be carried out using a computerized device.

RELATED APPLICATIONS

This application is related to and claims the benefit of U.S.Provisional Patent Application Ser. No. 61/456,029 titled FACILITATINGTHE INTEGRITY OF GOVERNMENT PAYMENTS BY USING PATTERNS OF BANKINGTRANSACTIONS AS A MEANS OF IDENTIFYING INDIVIDUALS TO BE EMPLOYED ATALEVEL THAT RENDERS THEM INELIGIBLE FOR SUCH PAYMENTS, filed on Nov. 1,2010, the entire contents of each of which are incorporated herein byreference.

FIELD OF THE INVENTION

The present invention relates to the field of analyzing data to producea request for an action and, more specifically, to access and interfacewith to be used to increase accuracy and efficiency of detectingineligibility to receive a benefit based on one or more rule.

BACKGROUND OF THE INVENTION

Federal and State governments employ a variety of programs to providesocial welfare to its citizens that may fall upon hard times. One suchgovernment financed social welfare program, as it is provided tocitizens of the United States, includes paying benefits paid tounemployed citizens that have became unemployed through no fault oftheir own. Other social welfare programs may be provided to citizens ofa country that are underpaid, or struggling to raise a family.Furthermore, a wide variety of additional governmental subsidies may bepaid to citizens due to their low income and/or employment status.Examples of such support include disability payments, unemploymentbenefits, retirement benefits, health care coverage and child supportpayments.

Unfortunately, a number of citizens may be receiving a benefit from thegovernmental social welfare programs despite their ineligibility toreceive such benefits. Governmental agencies providing the assistancehave traditionally been forced to rely on the allegations from anapplicant or beneficiary regarding his or her employment status,earnings, and other factors affecting eligibility to receive a benefit.The agencies have relied on self-reporting primarily because timelyinformation from independent sources had been unavailable. Further,during harder economic times, the volume of benefit receiving citizensmay be so high that it becomes burdensome to verify the eligibility ofthe citizens to receive the benefits.

Employment information from the state or National Directory of New HireDatabases, the Quarterly Earnings Reports, or the IRS may be up to 18months old by the time the information is reported to a governmentagency. Additionally, these sources of information cannot identifypotential beneficiaries that may be working “under the table,” or beingpaid in cash without reporting to an agency, such as the IRS or theSocial Security Administration. As a result, state and federal agenciesthat rely on self-reports from beneficiaries routinely pay benefits tobeneficiaries that are ineligible to receive them.

Payment integrity is compromised with the taxpayer picking up the tabfor erroneous claims. Whether deliberate fraud, errors, or inadvertentomissions, such payments to ineligible beneficiaries also create stressand burdensome paperwork for beneficiaries who may learn, months afterthe fact, that they are expected to repay money they have improperlyreceived, but have already spent. What is needed is a timely andindependent method of verifying employment and/or income streams thatwould reduce the frequency with which improper payments occur.

U.S. Pat. No. 7,818,188 to Allsup, et al. discloses a method ofrecovering overpayment of long-term disability benefits paid to aclaimant by a client after the receipt of Social Security disabilityinsurance payment. The Service Provider requests specific informationfrom the Social Security Administration regarding the award of SocialSecurity Disability Insurance benefits, and upon receiving thatinformation the Service Provider may determine the amount of theoverpayment. The payee will have previously authorized any overpaymentamount to be withdrawn electronically from his or her bank account.

Although the '188 patent is directed to reclaiming overpayment ofbenefits, it fails to seek relevant information, indicative of fraud onthe part of the recipient, or error on the part of the beneficiary orgovernment agency Furthermore, the '188 patent fails to perform aninvestigative identification of a pattern. In the '188 patent there isno investigation required, but rather the information as to the amountof overpayment is provided to the Service Provider who then simply takesthat information and implements a process for recovering theoverpayment.

U.S. Pat. No. 7,657,474 to Dybala, et al. discloses one such method forthe automated detection of selected patterns of financial transactionscharacterized as customer or trader behaviors and activities, andspecific events or sequence of events. The specific implementationrelates to identifying trading compliance violations for transactionsinvolving fixed income securities. In the '474 patent, common elementsare linked between multiple events, entities and activities. As theassociations extend beyond the original sources, the common elements maybe identified through direct or indirect association among the variousevents, entities and activities. Elements of interest may be retrieved,collected or processed from a general data source and may be stored in aseparate database or dataset. As additional elements are evaluated, thematches and the link between elements may also be stored. This processmay continue for the various elements and data sources.

The '474 patent, however, does not include a simple solution and,instead, requires application of complex rules that are specific to aparticular purpose of identifying trade violations. Furthermore, the'474 patent provides a proposed solution to a narrow problem, withlimited applicability and expandability to the effective detection ofineligible beneficiaries of benefits through social welfare programs.

U.S. Patent Application Publication No. 2010/0217701 to Mesilatydiscloses evaluating some or all past transactions of the customer andexecutes an analysis, including statistical calculations andevaluations, according to predefined methods and algorithms, to identifypatterns in the transactions of the customer's account. The patternsthat may be identified by the application may be further processed andanalyzed to produce a prediction sheet, which may estimate other futuretransactions of the customer's account.

However, the '701 patent limits review of the transactions provide apredictive analysis of future events, without determining the validityof past events. Although the '701 patent may engage in profiling tocreate a predictive analysis of what the banking transactions shouldlook like, it fails to provide a method to identify deviation from thatwhich would be considered anticipated behavior and also fails toindicate the potential ineligibility of a beneficiary. The '701 patentalso fails to disclose requesting a more thorough investigation upondetermining potential ineligibility of a beneficiary

It is already the case that government agencies such as the SocialSecurity Administration have, in 2011, began a national program tointerface with financial institutions across the country to verify theassets of recipients of Supplemental Security Insurance (SSI) benefitsand applicants for such benefits. Through a contractor, for example,Accuity, the Social Security Administration contacts banks in thegeographic area in which the beneficiary or applicant lives and requeststhat the financial organization search their databases for accounts thatmay be held by the SSI recipient or applicant. When accounts are found,the financial institution provides beginning and end of the monthbalances for the account holder. While this existing system may assistto verify the assets of a beneficiary, it lacks usefulness for verifyingthe employment status of the beneficiary, and thus the eligibility toreceive a benefit. The existence of current employment earnings, and theamount of those earnings, can be critical factors in determining ifapplicants are eligible for certain government benefits, or if thosealready receiving such benefits have become ineligible. As a result,there exists a need to determine the employment status of an intendedbeneficiary that is lacking in the prior art.

Therefore, there exists a need for a method and system for accessingrecords, such as from financial institutions, relating to a beneficiary,analyzing the records for patterns indicating employment at a level thatwould render the individual ineligible to receive a benefit, generatinga request for an action to be performed by an agency user, andperforming the action that may result in a government agency determiningthat the beneficiary has received improper payments.

SUMMARY OF THE INVENTION

With the foregoing in mind, the present invention advantageously allowsan agency to readily detect whether or not a beneficiary remainseligible to continue receiving the benefit, with an increased level ofefficiency and confidence over manual detection and self-reportedeligibility. The present invention may also advantageously be used todetermine whether or not a potential beneficiary is eligible to receivea benefit that the potential beneficiary is not yet receiving. Themethod and system according to an embodiment of the present invention isalso advantageously simple to install and user friendly.

These and other objects, features and advantages according to anembodiment of the present invention are provided by a method fordetermining ineligibility of a beneficiary receiving a benefit tocontinue to receive the benefit. The method may include accessing recorddata from a financial institution relating to banking transactions ofthe beneficiary. The method may additionally include analyzing therecord data to determine a pattern of the banking transactions for atime period prior to receiving the benefit that may be defined as apre-benefit pattern. The method may also include analyzing the recorddata to determine a pattern of banking transactions for a time periodafter receiving the benefit that may be defined as a post-benefitpattern. The method may then include identifying deviations between thepre-benefit pattern and the post-benefit pattern.

The method may also include applying a rule selected from a plurality ofrules to the deviations to determine noncompliance of the deviationswith the rule. The rules may be stored on a database and may beweighted, or ranked. The method may further include determining a levelof noncompliance of the deviations by ranking the noncompliance of eachdeviation to determine if the level of noncompliance is within a rangeof acceptable noncompliance. Compliance with the rule may result in noaction being taken. A level of noncompliance within the range ofacceptable noncompliance may additionally result in no action beingtaken. However, a level of noncompliance outside the range of acceptablenoncompliance may result in generating a request for an action to betaken, which may be provided to a user using a user interface.

According to an embodiment of the present invention, performing thesteps of the method, including accessing the record data, analyzing therecord data, identifying the deviations between the pre-benefit patternand the post-benefit pattern, applying the rule, determining the levelof noncompliance, and determining if the level of noncompliance iswithin the range of acceptable noncompliance may be carried out using acomputerized device.

The action that may be requested may be auditing the record datarelating to the beneficiary upon determining that the level ofnoncompliance is outside of the range of acceptable noncompliance.Additionally, the action requested may include auditing the record datarelating to the beneficiary upon determining that the level ofnoncompliance outside of the range of acceptable noncompliance is abovean audit threshold. An additional action may include communicating withthe beneficiary upon determining that the level of noncompliance withthe rules outside the range of acceptable noncompliance is below theaudit threshold.

According to an embodiment of the present invention, the record data mayinclude data that relates to a deposit of funds. Analyzing the recorddata may further include analyzing the data relating to the deposit toindicate the pattern of the banking transactions. Similarly, the recorddata may include data relating to a withdrawal of funds. Analyzing therecord data may further include analyzing the data relating to thewithdrawal to indicate the pattern of the banking transactions. Therecord data may include data relating to a deposit of funds and awithdrawal of funds. Analyzing the record data may further includeanalyzing the deposit and withdrawal to indicate the pattern of bankingtransactions.

The method may still further include providing the benefit to thebeneficiary upon determining that the level of noncompliance is withinthe range of acceptable noncompliance. The method may also includedefining a savings to include a difference between the benefit providedto the beneficiary prior to the benefit being denied and the benefitprovided to the beneficiary subsequent to the benefit beings beingdenied. Thereafter, a portion of the savings may be shared with a thirdparty.

The computerized device may include a network interface that connects toa network, and the method may also include communicating with a bankingcomputerized device through the network. The method may further includecommunicating with a record custodian computerized device through thenetwork. The computerized device may additionally access a status recordindicative of ineligibility to receive the benefit from the recordcustodian computerized device. The status record may include evidence ofthe level of noncompliance with the rules.

Machine learning may be used to determine whether the level ofnoncompliance with the rules is within the range of acceptablenoncompliance. This may include receiving feedback relating to anaccuracy of the determination of ineligibility of the beneficiary,accessing the feedback prior to generating a subsequent request for theaction, and analyzing the feedback to improve the accuracy of thesubsequent request for the action. The feedback may be indicative of theaccuracy of a prior recommended action.

A system may also be provided for determining ineligibility of abeneficiary receiving a benefit to continue to receive the benefit. Thesystem may include a network interface on a computerized device thatconnects to a network. The computerized device may include a memory anda processor. A banking computerized device in communication with thenetwork may be included. Record data from a financial institutionrelating to banking transactions of the beneficiary may be accessedusing the computerized device. Additionally, the record data may beanalyzed using the computerized device to determine a pattern of thebanking transactions. In an embodiment of the present invention, theanalysis may be completed within the financial institution usinginformation on suspect beneficiaries, which may be potentiallyineligible to receive the benefit, being the only information beingintercommunicated between the financial institution and the governmentagency.

A rule may be selected from a plurality of rules stored on a database.The rule may be applied to the pattern of the banking transactions usingthe computerized device to determine a level of noncompliance. The levelof noncompliance of the pattern may be determined to be within a rangeof acceptable noncompliance using the computerized device. Compliancewith the rule may result in no action being taken. A level ofnoncompliance within the range of acceptable noncompliance may alsoresult in no action being taken. Alternatively, a level of noncomplianceoutside the range of acceptable noncompliance may result in generating arequest using the computerized device for an action to be taken. Therequest for the action to be taken may be provided to a user using auser interface.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of the system for determining ineligibility ofa beneficiary receiving a benefit to continue to receive the benefit,according to an embodiment of the present invention.

FIG. 2 is a block diagram of a computerized device that may be includedin the system illustrated in FIG. 1.

FIG. 3 is a flowchart illustrating general operation of the systemillustrated in FIG. 1.

FIG. 4 is a flowchart illustrating detection and analysis of patterns inrecord data, according to an embodiment of the present invention.

FIG. 5 is a flowchart illustrating a strength based analysis ofpatterns, according to an embodiment of the present invention.

FIG. 6 is a timeline illustrating a time period prior to receiving thebenefit and a time period following receiving the benefit, according toan embodiment of the present invention.

FIG. 7 is a flowchart illustrating analyzing deposits with a pre-benefitpattern, according to an embodiment of the present invention.

FIG. 8 is a flowchart illustrating analyzing withdrawals with apre-benefit pattern, according to an embodiment of the presentinvention.

FIG. 9 is a flowchart illustrating analyzing feedback, according to anembodiment of the present invention.

FIG. 10 is a flowchart illustrating use of feedback to increase theaccuracy of recommending actions, according to an embodiment of thepresent invention.

FIG. 11 is a flowchart illustrating calculating savings, according to anembodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention will now be described more fully hereinafter withreference to the accompanying drawings, which preferred embodiments ofthe invention are shown. This invention may, however, be embodied inmany different forms and should not be construed as limited to theembodiments set forth herein. Rather, these embodiments are provided sothat this disclosure will be thorough and complete, and will fullyconvey the scope of the invention to those skilled in the art. Those ofordinary skill in the art realize that the following descriptions of theembodiments of the present invention are illustrative and are notintended to be limiting in any way. Other embodiments of the presentinvention will readily suggest themselves to such skilled persons havingthe benefit of this disclosure. Like numbers refer to like elementsthroughout.

In this detailed description of the present invention, a person skilledin the art should note that directional terms, such as “above,” “below,”“upper,” “lower,” and other like terms are used for the convenience ofthe reader in reference to the drawings. Also, a person skilled in theart should notice this description may contain other terminology toconvey position, orientation, and direction without departing from theprinciples of the present invention.

Additionally, in the following disclosure, a user interface may bediscussed through which a user may interact with the system 10 disclosedherein. The user interface may be one of a plurality of computerizedinterfaces, including monitors, screens, audio alerts, or otherelectronically generated communications that may be used to provide auser with information. A user interface may additionally include printeddocuments, paper reports, supplemental inserts to be included withinexisting reports, and related memoranda. Skilled artisans willappreciate a user interface to generally include any object or device,electronic or not, that may be capable of informing a user of one ormore parameters determined by the system 10.

Referring now to FIGS. 1-11, a system 10 for detecting the ineligibilityof a beneficiary according to the present invention is now described ingreater detail. Throughout this disclosure, the system 10 for detectingthe ineligibility of a beneficiary may also be referred to as anineligibility detection system, a system, or the invention. Alternatereferences of the system 10 in this disclosure are not meant to belimiting in any way. A person of skill in the art will appreciate that,although the present invention is described herein for determining, withan increased level of efficiency and confidence over manual detectionand self-reported eligibility, that a beneficiary may likely beineligible to receive a benefit relating to government funded socialwelfare programs, the present invention should not be limited to suchpublic programs. For example, and without limitation, the system 10 ofthe present invention may be additionally used to analyze records toidentify patterns, such as banking transactions, that indicateineligibility, or requirements to pay, relating to child supportpayments, disability, alimony, judgments, bankruptcy, or virtually anyother program wherein a participant may be determined to be ineligibleto receive a benefit upon failure to comply with a condition. Further,the system 10 of the present invention is not mean to be limited to usein the United States. Instead, the system 10 of the present invention issuitable to be used in connection with any agency throughout the worldthat provides various types of benefits to its citizens, or for privateindustries that provide certain benefits to its employees.

In the following disclosure, various elements may be described tomanipulate and analyze data stored within one or more database. As wouldbe appreciated by a person of skill in the art, these elements may beoperated on a computerized device 110. A person of skill in the art willa appreciate that the database may be included in a database server,which may include one or more additional databases collectively orindependently accessed and analyzed by a computerized device 110.Additionally, the various illustrative program modules and stepsdisclosed herein may be implemented via electronic hardware, computersoftware, or combinations of both. The various illustrative programmodules and steps have been described generally in terms of theirfunctionality. Whether the functionality is implemented as hardware orsoftware depends, in part, upon the hardware constraints imposed on thesystem 10. Hardware and software may be interchangeable depending onsuch constraints.

Provided as a non-limiting example, the various illustrative programmodules and steps, described in connection with the embodimentsdisclosed herein, may be implemented or performed via a computerizeddevice 110. Such computerized devices 110 may include, but should not belimited to, an application specific integrated circuit (ASIC), a fieldprogrammable gate array (FPGA), other programmable logic device,discrete gate logic, transistor gate logic, discrete hardwarecomponents, conventional programmable software module and a processor,or any combination thereof that may be designed to perform the functionsdescribed herein.

The system 10 of this disclosure may advantageously facilitate theconsistent, accurate, and expedited assessment as to whether or not abeneficiary is probably eligible to continue receiving a benefit, i.e.,the system 10 and method according to an embodiment of the presentinvention advantageously identifies patterns of banking transactionsthat may indicate probable ineligibility of a beneficiary to continuereceiving a benefit. After detecting the pattern, the system 10 maygenerate a request for an action to be performed by the agency. Theaccuracy of the pattern detection that may lead to the requests may bedynamically improved through machine learning. These advantages andfeatures will be discussed in greater detail throughout the followingdisclosure. Those skilled in the art will appreciate that the patterndetection may be provided using an algorithm that may lead to a requestfor the action to be performed by the agency.

The system 10 of the present invention may be considered an employmentdetection system. In other words, the system according to the presentinvention advantageously detects employment earnings via an analysis ofdeposit records from the beneficiary's financial institution. Althoughthis specification describes the analysis of banking transactions, it ispreferred that deposits made into the financial institution of thebeneficiary be analyzed to assess a probability of whether or not thebeneficiary is receiving compensation while simultaneously receiving thebenefit and, if so, whether or not that compensation rises to a level tomake the beneficiary ineligible to receive the benefit.

Referring now to FIG. 1, the system 10 of the present invention will nowbe discussed. The system 10 may include a computerized device 110communicable with additional computerized devices 110 over a network 175connection. The additional computerized devices 110 may include, forexample and without limitation, a banking computerized device 111 and/ora record custodian computerized device 112. The computerized device 110may additionally include, or be communicatively connected to, a database101. The computerized device 110 may access and analyze a record todetermine whether a beneficiary is ineligible to receive a benefit. Moreparticularly, the system 10 and method according to an embodiment of thepresent invention advantageously allows for an assessment to be made asto whether or not a beneficiary that is currently receiving a benefit islikely to be eligible to receive a benefit, or whether a potentialbeneficiary that desires to receive a benefit is eligible to receivesuch a benefit. The analysis may include detecting one or more patternsin the record data, assigning a strength to a respective pattern, anddetermining the accuracy of the assessment by having the user agencyfollow-up to verify whether the pattern detected was, in fact, relatedto employment by the beneficiary at a level that would render thebeneficiary ineligible to receive certain benefits.

When determining a pattern, several different critical variables may beanalyzed. For example, the critical variables may include the size of adeposit, the interval of deposits, the source of deposits, or any othernumber of specific critical variables as may be understood by theskilled artisan. In addition, the existence of a deposit streampre-benefit period can rule out its potential relevance in apost-benefit period. The following examples are not meant to be limitingin any way, but are provided for clarity of the types of variables thatare considered when analyzing the record data to determine a pattern. Inone example, the system 10 may analyze deposits made prior to thebeneficiary receiving the benefit and deposits made after receiving thebenefit to determine a respective pre-benefit pattern and a post-benefitpattern. In some instances, the system 10 may be attempting to identifydeposits that may be out of the ordinary with respect to the size of thedeposit, the intervals between deposits, e.g. the frequency of deposits,the source of the deposits, or any other number of critical variablesrelating to deposits that may be analyzed to determine a depositpattern. The deposit pattern may be analyzed with respect to certainthresholds that may be set to determine whether or not the depositpattern is in compliance with certain standards, or rules. With respectto intervals of deposits, if, for example, the intervals of depositsafter the beneficiary has started to receive a benefit, is consistentwith a profile of a beneficiary that has a job and deposits are made,also for example, weekly or biweekly, then an indication ofnoncompliance, or some level of noncompliance, may be provided by thesystem 10. In this disclosure, the terms frequency and interval whenrelating to deposits can be interchangeably used. In other words, thesystem 10 according to an embodiment of the present invention mayconduct an analysis of the frequency of deposits made into an account ofa beneficiary, or the interval between when deposits are made into anaccount of a beneficiary. If the frequency of the deposits, or theinterval between when the deposits are made are similar to thoseindicating employment, e.g., a weekly deposit that is similar, or abi-weekly deposit that is similar which may indicate a steady paycheck,then an indication of noncompliance, or a level of noncompliance may beprovided. Similarly, if the amounts of the deposits are indicative ofsignificant work activity, or if there is an indication of a depositpattern indicative of employment started post-benefit period, then anindication of noncompliance, or some level of noncompliance, may beprovided. This type of analysis can occur for any number of variablesassociated with a deposit, or any number of variables associated withany banking transaction.

Those skilled in the art will also appreciate that routine bankingactivity may also be monitored to ensure that the beneficiary remainseligible to receive a benefit. For example, the present inventionadvantageously contemplates that activities relating to cashing checksat the beneficiary's financial institution may be considered whendetermining a banking transaction to provide evidence of under the tableemployment related income.

Continuing to reference FIG. 1, a general architectural structure of thesystem 10 will now be discussed. The system 10 may include acomputerized device 110, a database 101, and/or a network 175 connectivestructure to communicate data with one or more connected computerizeddevice 110. The computerized device 110 may further include a processor120, memory 130, input/output (I/O) interface 160, and a networkinterface 170, which may be communicatively connected to one another viaa bus 121. The processor 120 may be a microprocessor, CPU, controller,microcontroller, programmable logic device, array of logic elements, orstate machine. A person of skill in the art will appreciate additionaldevices that may accept and process digital logic commands to produce aresult to be included as a processor 120, as defined herein.

The computer may additionally include memory 130, which may be used tostore and read one or more software module. The memory 130 may includerandom access memory (RAM), flash memory, read only memory (ROM),erasable programmable read only memory (EPROM), electrical erasableprogrammable read only memory (EEPROM), hard disk, removable disk, CD,DVD or any other form of storage medium known in the art. As will beappreciated by skilled artisans, a processor may be operativelyconnected to the storage medium to read and write information to andfrom the storage medium, respectively. Alternately, at least part of thememory 130 may be integrated into the processor 120.

The I/O interface 160 may be used to send and receive datacommunications between one or more external device. The I/O interface160 may additionally be connected to the processor 120, memory 130, andother components of the computerized system 10 110 via the bus 121. Aperson of skill in the art will appreciate that additional embodimentsare contemplated in which the I/O may be directly connected to thememory 130, processor 120, or other component, which are intended to beincluded within the scope and spirit of the present invention. FIG. 1illustrates an example of the I/O interface 160 being connected betweena bus 121 and the database 101. Skilled artisans will appreciateadditional computerized devices 110 and components that may be connectedto the present computerized device 110 through the I/O interface 160.

The computerized device 110 may additionally include a network interface170, through which the present device may communicate with additionalcomputerized devices 110 through a network 175, such as, for example, abanking computerized device 111 or a record custodian computerizeddevice 112. A banking computerized device 111 may be a computerizeddevice 110 that includes financial records and/or banking transactionsrelating to a beneficiary. A record data computerized device 112 may bea computerized device 110 that includes status records, such asemployment records and/or other record data that may relate to theineligibility of a beneficiary to receive a benefit. The computerizeddevice 110 may additionally be connected to a database 101 via thenetwork 175. The network 175 include a data communication pathway,though which a plurality of computerized devices 110 may exchange data,including the banking computerized device 111 and the record datacomputerized device 112.

The database 101 may be understood as a collection of data, which may beorganized. The database 101 may include one or more additional database,which may include a subset of data generally included in the database101. Examples of additional databases may include a rules database 103,profiles database 104, actions database 105, and an optional accuracydatabase 106. The rules database 103 may include rules to be performedand analyzed by a rules engine, which may be operated by a computerdevice. The rules may be ranked, for example, respective to theimportance of the rule in determining ineligibility to receive abenefit. The profiles database 104 may include data relating to abeneficiary. The actions database 105 may include one or more actionsthat may be suggested by the system 10 based on a range ofnoncompliance. An accuracy database 106 may additionally include datarelating to accuracy of previous recommendations, which data may be usedto improve the accuracy of future recommendation made by the system 10of the present invention.

FIG. 2 illustrates a detailed block diagram of an embodiment of atypical computerized device 110, which is capable of performing one ormore computer-implemented steps in practicing the method aspects of thepresent invention. Components of the computerized device 110 mayinclude, but are not limited to a processing unit 120, a system memory130, and a system bus 121 that couples various system componentsincluding the system memory to the processing unit 120. The system bus121 may be any of several types of bus structures including a memory busor memory controller, a peripheral bus, and a local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus also known as Mezzanine bus.

The computerized device 110 may also include a cryptographic unit 125.Briefly, the cryptographic unit 125 has a calculation function that maybe used to verify digital signatures, calculate hashes, digitally signhash values, and encrypt or decrypt data. The cryptographic unit 125 mayalso have a protected memory for storing keys and other secret data. Inother embodiments, the functions of the cryptographic unit may beinstantiated in software and run via the operating system.

A computerized device 110 typically includes a variety of computerreadable media. Computer readable media can be any available media thatcan be accessed by a computerized device 110 and includes both volatileand nonvolatile media, removable and non-removable media. By way ofexample, and in no way meant to be limiting, computer readable media mayinclude computer storage media and communication media. Computer storagemedia includes volatile and nonvolatile, removable and non-removablemedia implemented in any method or technology for storage of informationsuch as computer readable instructions, data structures, program modulesor other data. Computer storage media includes, but is not limited to,RAM, ROM, EEPROM, FLASH memory or other memory technology, CD-ROM,digital versatile disks (DVD) or other optical disk storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can accessed by a computerized device 110.Communication media typically embodies computer readable instructions,data structures, program modules or other data in a modulated datasignal such as a carrier wave or other transport mechanism and includesany information delivery media. The term “modulated data signal” refersto a signal that has one or more of its characteristics set or changedin such a manner as to encode information in the signal. By way ofexample, and not limitation, communication media may include wired mediasuch as a wired network or direct-wired connection, and wireless mediasuch as acoustic, radio frequency, infrared and other wireless media.Combinations of any of the above should also be included within thescope of computer readable media.

The system memory 130 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) 131and random access memory (RAM) 132. A basic input/output system 133(BIOS), containing the basic routines that help to transfer informationbetween elements within computerized device 110, such as duringstart-up, is typically stored in ROM 131. RAM 132 typically containsdata and/or program modules that are immediately accessible to and/orpresently being operated on by processing unit 120. By way of example,and not limitation, FIG. 2 illustrates an OS 134, application programs135, other program modules 136, and program data 137.

The computerized device 110 may also include otherremovable/non-removable, volatile/nonvolatile computer storage media. Byway of example only, FIG. 2 illustrates a hard disk drive 141 that readsfrom or writes to non-removable, nonvolatile magnetic media, a magneticdisk drive 151 that reads from or writes to a removable, nonvolatilemagnetic disk 152, and an optical disk drive 155 that reads from orwrites to a removable, nonvolatile optical disk 156 such as a CD ROM orother optical media. Other removable/non-removable, volatile/nonvolatilecomputer storage media that can be used in the exemplary operatingenvironment include, but are not limited to, magnetic tape cassettes,flash memory cards, digital versatile disks, digital video tape, solidstate RAM, solid state ROM, and the like. The hard disk drive 141 istypically connected to the system bus 121 through a non-removable memoryinterface such as interface 140, and magnetic disk drive 151 and opticaldisk drive 155 are typically connected to the system bus 121 by aremovable memory interface, such as interface 150.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 2, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputerized device 110. In FIG. 2, for example, hard disk drive 141 isillustrated as storing an OS 144, application programs 145, otherprogram modules 146, and program data 147. Note that these componentscan either be the same as or different from operating system 134,application programs 135, other program modules 136, and program data137. The OS 144, application programs 145, other program modules 146,and program data 147 are given different numbers here to illustratethat, at a minimum, they are different copies. A user may enter commandsand information into the computerized device 110 through input devicessuch as a keyboard 162 and cursor control device 161, commonly referredto as a mouse, trackball or touch pad. Other input devices (not shown)may include a microphone, joystick, game pad, satellite dish, scanner,or the like. These and other input devices are often connected to theprocessing unit 120 through a user input interface 160 that is coupledto the system bus, but may be connected by other interface and busstructures, such as a parallel port, game port or a universal serial bus(USB). A monitor 191 or other type of display device is also connectedto the system bus 121 via an interface, such as a graphics controller190. In addition to the monitor, computers may also include otherperipheral output devices such as speakers 197 and printer 196, whichmay be connected through an output peripheral interface 195.

The computerized device 110 may operate in a networked environment usinglogical connections to one or more remote computers, such as a remotecomputer 180. The remote computer 180 may be a personal computer, aserver, a router, a network PC, a peer device or other common networknode, and typically includes many or all of the elements described aboverelative to the computerized device 110, although only a memory storagedevice 181 has been illustrated in FIG. 2. The logical connectionsdepicted in FIG. 2 include a local area network (LAN) 171 and a widearea network (WAN) 173, but may also include other networks 175. Suchnetworking environments are commonplace in offices, enterprise-widecomputer networks, intranets and the Internet.

When used in a LAN networking environment, the computerized device 110is connected to the LAN 171 through a network interface 170 or adapter170. When used in a WAN networking environment, the computerized device110 typically includes a modem 172 or other means for establishingcommunications over the WAN 173, such as the Internet. The modem 172,which may be internal or external, may be connected to the system bus121 via the user input interface 160, or other appropriate mechanism. Ina networked environment, program modules depicted relative to thecomputerized device 110, or portions thereof, may be stored in theremote memory storage device. By way of example, and not limitation,FIG. 2 illustrates remote application programs 185 as residing on memorydevice 181.

The communications connections 170, 172 allow the device to communicatewith other devices. The communications connections 170, 172 are anexample of communication media. The communication media typicallyembodies computer readable instructions, data structures, programmodules or other data in a modulated data signal such as a carrier waveor other transport mechanism and includes any information deliverymedia. A “modulated data signal” may be a signal that has one or more ofits characteristics set or changed in such a manner as to encodeinformation in the signal. By way of example, and not limitation,communication media includes wired media such as a wired network ordirect-wired connection, and wireless media such as acoustic, RF,infrared and other wireless media. Computer readable media may includeboth storage media and communication media.

According to an embodiment of the present invention, a computer programproduct is disclosed, which may detect a potentially ineligiblebeneficiary that may be receiving a benefit. A computer program product,according to an embodiment of the present invention, will be describedin further detail as a project that is creatable using, for example, butnot intended as a limitation, Microsoft's Visual C# .NET developmentenvironment. Such a computer program product would be suitable forexecution on a computerized device 110 having, for example, but notintended as a limitation, one of Microsoft's Windows family of operatingsystems loaded into memory 134. A person having skill in the art, afterhaving the benefit of this disclosure, would recognize that many otherdevelopment platforms might be used to perform the computerized methodsdisclosed herein, which may be executable with many other operatingsystems, but that still embody the present invention. As such, thefollowing disclosure is provided merely for explanatory purposes andshould in no way limit the present invention to computer programproducts that are created using the aforementioned development platformor for use with the aforementioned operating systems.

Referring now to flow chart 200 of FIG. 3, an illustrative methodoperation for generally assessing a beneficiary that may be ineligibleto receive a benefit according to an embodiment of the present inventionwill now be discussed. Starting at Block 202, the system 10 may accessrecord data relating to beneficiary (Block 204). The record data may beretrieved from a financial institution that may be connected through anetwork 175 using a computerized device that may also be connected tothe network. The financial institution may include a bankingcomputerized device 111 to communicate the record data. The system 10may perform a computerized analysis on the record data (Block 206). Thecomputerized analysis may, for example, process the data, search forpatterns, or perform other analyses that would be appreciated by skilledartisans. Due to financial privacy concerns, financial transactions andother banking data relating to the beneficiary may remain within thebank systems, with only those beneficiaries whose patterns of bankingtransactions are indicative of noncompliance being identified to thegovernment agency requesting the information. Of course, this inventionis not to be limited based on individual policies of certain financialinstitutions with respect to release, or sharing, of informationrelating to a beneficiary. This is meant merely for exemplary purposes.The system 10 of the present invention contemplates that data relatingto financial transactions of a beneficiary may be downloaded from afinancial institution and stored on a separate server that is associatedwith providing a benefit.

After the record data has been analyzed, the system 10 may generate aproposed request for an action (Block 208). The requested actiongenerated by the system 10 may be dependent upon the analysis performedat Block 206. The requested action may be performed by a user, such asan agency (Block 210). As an example, and without limitation, the agencymay include the Social Security Administration, which may perform theaction of auditing the account of a beneficiary to make a finaldetermination regarding ineligibility to receive a benefit.

Referring now to flow chart 220 of FIG. 4, an illustrative methodoperation for analyzing record data to recommend an action according toan embodiment of the present invention will now be discussed. A personof skill in the art will appreciate additional methods of analyzingrecord data, some of which will be discussed within this disclosure, tobe included within the scope and spirit of the present invention.Starting at Block 222, the system 10 may access record data relating toa beneficiary from a financial institution (Block 224). The record datamay relate to banking transactions, among other things. The system 10may then analyze the banking transactions included in the record data todetect patterns (Block 226).

If it is determined at Block 228 that no pattern consistent withpost-benefit employment by the beneficiary exists, or consistent withthe existence of a new revenue stream for the beneficiary, the operationmay terminate at Block 236. However, if it is determined at Block 228that a pattern does exist, the system 10 may analyze the pattern todetermine the likelihood of employment or the existence of an unreportedasset possessed by a beneficiary (Block 230). After the system 10analyzes the pattern, it may determine whether the beneficiary is likelyto have employment earnings and/or unreported assets, which could renderthe beneficiary ineligible to receive the benefit (Block 232). If thepatterns, which may be indicated by the banking transaction, show that abeneficiary is not likely to be employed, or does not likely haveunreported assets, the operation may terminate at Block 236. Conversely,if the beneficiary is likely employed, or likely has unreported assets,the system 10 may perform a requested action (Block 234). The requestedaction may, for example, be to generate a recommendation to audit thebeneficiary. A person of skill in the art will appreciate thatadditional recommendations and/or actions may be generated by the system10 as a result of a detected pattern, such as, for example, sending awarning communication to the beneficiary, or a request that thebeneficiary contact the agency to provide an explanation for the suspectpattern as included in the scope of the present invention. The operationmay then terminate at Block 236.

Referring now additionally to flow chart 240 of FIG. 5, an illustrativemethod operation for determining an action to recommend relating to alevel of noncompliance with a rule according to an embodiment of thepresent invention is now described in greater detail. Starting at Block242, the system 10 may access record data relating to a beneficiary(Block 244). The system 10 may then analyze each item of record dataincluded in the record relating to the beneficiary. More specifically,the system 10 may analyze a first item of record data to determinewhether the item is noncompliant with the rules (Block 246). The system10 may next assign a measurement of strength to the item of record datarelating to noncompliance with the rule (Block 248). The strength of therule may be related to the ranking of the rule, which may indicate theimportance of the rule in determining whether a beneficiary may beineligible to receive a benefit.

The system 10 according to the present invention may include severaldifferent types of rules that are used to detect compliance ornoncompliance of a detected pattern relating to the beneficiary'sbanking transactions. The banking transactions, as indicated above, areprovided as part of the record data that may be retrieved from thefinancial institution, or a records custodian, or analyzed while in thecustody of the financial institution at the request of the governmentagency. The rules may be used to analyze a pattern of deposits that aremade into the beneficiary's bank account. More specifically, withoutlimitation, the rules may be used to analyze the amount of the deposits,the source of deposits and the intervals between deposits to assess thelikelihood that the pattern is indicative of employment that may exceedan allowable threshold. The present invention also contemplates thatdeposit patterns that are probably indicative of a spouse's employmentearnings which may be deposited into a bank account shared with thebeneficiary, or income from other sources such a loans, trust fundpayments, support from family etc, may be excluded from analysis. Toaccomplish this, a comparison of pre-benefit deposit patterns may bemade with post-benefit deposit patterns. If the suspect deposit patternexisted before the benefit was started, then it may likely be anallowable income stream. If a new deposit stream begins after the startof benefits, then this may be an indication of employment, and thereforeindicative of possible improper payments.

Those skilled in the art will appreciate that a similar analysis mayoccur with respect to withdrawals, i.e., a beneficiary's withdrawaltransactions may also be analyzed in order to determine whether or notthe withdrawal activity is indicative of employment, or another revenuestream, that may lead to an indication that the beneficiary is noteligible to receive the benefit. Therefore, the system 10 according tothe present invention contemplates analyzing a pattern of withdrawals,analyzing a bank balance of the beneficiary, analyzing the originationof deposits, analyzing the types of payment made, analyzing theintervals between deposits or withdrawals, analyzing the size ofdeposits or withdrawals, or any analysis of any banking transaction thatmay indicate a pattern of behavior of the beneficiary with respect tothe financial transactions of the beneficiary, as understood by thoseskilled in the art.

The system 10 may then determine whether all items of record data havebeen analyzed (Block 250). If items of record data remain to beanalyzed, the system 10 may access the next item of record data (Block252). The system 10 may then again proceed to perform the operation ofBlock 248, wherein it may assign a measurement of strength to the itemof record data relating to noncompliance with the rule. Once the system10 determines that all the items of record data have been analyzed atBlock 250, the system 10 may rank the strengths assigned to the items ofrecord data to determine a level of noncompliance of the beneficiarywith the rules (Block 254).

As a specific example of the operation of flow chart 240, providedwithout limitation, the system 10 may determine at Block 254 that abeneficiary's account is noncompliant with at least one rule. However,the rule may not be ranked as highly important. As a result, the system10 may indicate that; although the record data relating to a beneficiaryis noncompliant with at least one rule, the level of noncompliance islow. Conversely, if the rule were ranked as highly important, the system10 may indicate a high level of noncompliance upon the beneficiary beingnoncompliant with a single, highly important rule.

If it is determined at Block 256 that the level of noncompliance withthe rules is high, the system 10 may generate a request for an audit ofthe account associated with the beneficiary (Block 258). Conversely, ifit is determined that the level of noncompliance with the rules is low,the system 10 may generate a request for no action to be taken (Block260). A plethora of optional intermediate threshold levels ofnoncompliance with the rules may result in the generation of requestsfor different actions. The system 10 may additionally define a range ofacceptable noncompliance, which may analyze whether the noncompliancewith the rules reaches a level of noncompliance that would result ingenerating a particular action.

As an example, provided without limitation, the system 10 may include anintermediate level of noncompliance with the rules, which may include alevel of noncompliance that is above the low level but below the highlevel of noncompliance. Upon determination that the record data isindicative of an intermediate level of noncompliance with the rules, thesystem 10 may generate a request for a communication to be sent to theclient (Block 262). Such communication may include educational materialsto inform the beneficiary as to their responsibilities to promptlyreport employment earnings, or other requirements to be eligible toreceive the benefit. Alternatively, the communication may include awarning that the record data associated with the beneficiary isindicative of noncompliance with the rules, such as being employed. Thewarning communication may additionally require the beneficiary tocontact the government agency administering the benefits to explain thesuspect patterns. The communication may also indicate that furthernoncompliance with the rules may result in the recommendation of anotheraction, such as an audit. Such communication may require the beneficiaryto provide an explanation of the suspect pattern or face suspension ofbenefits. The suspension may be immediate, or may take place over a timeperiod. Those skilled in the art will appreciate that the system 10according to the present invention contemplates that a suspension, ifnecessary, may automatically occur, or the beneficiary may, for example,be warned (possibly multiple times) that a lack of explanation of apattern may result in a suspension of benefits as of a particular date.Automated communication systems may be used to minimize the need forexpensive labor intensive interactions with agents, or othergovernmental employees, or other employees responsible for distributingand monitoring the benefits. Many false alerts can be dealt with easilyby having the beneficiary call an Interactive Voice Response system, forexample, and simply explain the suspect pattern.

The system 10 may then determine whether a shutdown command has beenreceived (Block 264). If no shutdown command has been received, thesystem 10 may return to the operation of Block 244, wherein it mayaccess the record data of a beneficiary. A person of skill in the artwill appreciate that the subsequent performance of the operationincluded in Block 244 may relate to accessing the record data of one ormore different beneficiaries, or the previously analyzed beneficiary. Ifa shutdown command has been received at Block 264, the operation mayterminate at Block 266.

Referring now to the timeline 270 of FIG. 6, an embodiment of ananalysis will now be discussed to determine noncompliance with one ormore rule. More specifically, analysis relating to a bankingtransactions timeline will now be discussed. A person of skill in theart will appreciate that analyzing the record data with respect to thebanking transactions timeline is provided herein as an example, and thatadditional analyses may occur to determine whether record data iscompliant with the rules. Additionally, skilled artisans will appreciatethat the banking transactions timeline is presented relative toreceiving unemployment benefits, and different benefits may havediffering timelines respective to the benefit.

The banking transactions timeline may include one or more event 272 thataffects the analysis of the record data relating to a beneficiary. Inthe example of receiving unemployment benefits, an event 272 may includethe commencement of unemployment benefits. The banking transactions thatmay have occurred prior to the event 272 may establish a time periodprior to receiving a benefit 274, or a series of transactions prior therequirement of compliance with a condition. The banking transactionsthat may occur subsequent to the event 272 may be included in a timeperiod following receiving the benefit 276, wherein noncompliance withthe rules may make a beneficiary ineligible to receive the benefit. Aperson of skill in the art will appreciate that the record data may beanalyzed to determine noncompliance with conditions, respective to thetimeline 272 depicted in FIG. 6, among other factors.

Referring now to flowcharts 280 and 330, of FIGS. 7 and 8, respectively,will now be discussed. More specifically, illustrative examples ofanalyses that may compare record data including one or more pre-benefitpattern to record data that include one or more post-benefit patternwill now be discussed. The pre-benefit pattern may relate to depositsand/or withdrawals that occur in the time period prior to receiving abenefit 274. Similarly, the post-benefit pattern may relate to depositsand/or withdrawals that occur in the time period following receiving thebenefit 276. The pre-benefit pattern and the post-benefit pattern may becompared to determine deviations between each other. Deviations may beindicative of noncompliance with the rules,

Referring now to flowchart 280 of FIG. 7, an illustrative example of ananalysis operation to determine whether a beneficiary is ineligible toreceive a benefit will now be discussed. More specifically, anillustrative example of an analysis that compares record data relatingto deposits that occurs in the time period prior to receiving a benefit274 to record data that occurs in the time period following receiving abenefit 276 to determine noncompliance with the rules will now bediscussed. Starting at Block 282, the system 10 may determine apre-benefit pattern, or baseline (Block 284). The baseline may bedetermined, for example, by analyzing banking transactions, such asdeposits, that may occur prior to the event, i.e., prior to a claim forbenefits is made. A person of skill in the art will additionallyappreciate analyses that may be used to determine a baseline to beincluded herein.

Once a baseline has been established at Block 284, the system 10 mayaccess the record data of the beneficiary. Skilled artisans mayappreciate that the record data may additionally be accessed prior toestablishing the baseline in order to access the record data used toestablish the baseline. Additionally, the record data may be accessedsubsequently or periodically to perform the actions of flowchart 280 atanother time.

Once the record data of the beneficiary has been accessed at Block 286,the system 10 may analyze the record (Block 288). The system 10 maydetermine from the analysis whether a deposit included in the recordexceeds a threshold (Block 290). The threshold may be predetermined,manually adjustable, dynamical adjustable, scaling, or otherwisevariable. If the deposit being examined does not exceed the threshold,the operation may continue to Block 318, wherein it may be determinedwhether a shutdown command has been received. However, if a deposit isdetected that may exceed the threshold at Block 290, the system 10 mayexamine the source of the deposit (Block 292).

The system 10 may determine whether the deposit source is invalid (Block294). If it is determined that the deposit source is not invalid, thesystem 10 may next determine whether the deposit source includes anindication of an automated clearing house (ACH) deposit, or otherwiseautomated deposit (Block 298). However, if it is determined at Block 294that the deposit source appears to be invalid, the system 10 may nextdetermine whether the deposit source is likely a payroll deposit. Aperson of skill in the art will appreciate payroll deposits to includeregular deposits of similar amounts, deposits that include a phrase suchas “payroll,” or other indicators that would apparent after having thebenefit of this disclosure. If it is determined at Block 296 that thedeposit is clearly payroll, the system 10 may perform the operation ofBlock 306, wherein it may compare the pattern of the deposit to thebaseline. If the particular deposit pattern existed during thepre-benefit period it can be eliminated from suspicion. The system 10can determine that a deposit pattern which existed during thepre-benefit period may likely constitute employment funds coming in foranother account holder sharing the account, or funds that are notemployment related and of no interest to the agency distributing thebenefit. If it is determined at Block 296 that the deposit source is notclearly payroll at Block 296, the operation may proceed to Block 298wherein it may be determined whether the deposit is an ACH deposit.

If the system 10 determines that the deposit is not an ACH deposit, itmay determine whether the deposits are made at approximately regularintervals (Block 304). Alternatively, if the system 10 determines thatthe deposit is an ACH deposit, or an otherwise automated deposit, atBlock 298, the system 10 may increase the strength of the pattern (Block300) before continuing to the operation of Block 304.

If the system 10 determines that deposits are not made at approximatelyregular intervals at Block 304, it may compare the pattern of thedeposits to the baseline (Block 306). The comparison between the patternand the baseline may consider the relevance, or strength, of the patternto the agency that is distributing the benefit. Alternatively, if thesystem 10 determines that the deposits are made at approximately regularintervals, or that deposits are made at approximately regular intervalsand have a size that may be determined to be significant, or otherwiseindicative of a suspect pattern of deposits, at Block 304, the system 10may decrease the strength of the pattern (Block 302) before continuingto the operation of Block 306.

After comparing the pattern to the baseline, the system 10 may determinewhether the pattern is indicative of employment (Block 308). Thisdetermination may weigh the strengths of the patterns with the rankingof the rules. If the pattern is not indicative of employment, the system10 may proceed to the operation of Block 318, wherein it may determinewhether a shutdown command has been received. Alternatively, the system10 may generate a recommendation that no action be taken in regard tothe beneficiary, for example, by recommending that the beneficiary notbe audited. However, if the pattern is indicative of employment at Block308, the system 10 may determine the strength of the pattern todetermine whether an audit should be requested (Block 310).

If it is determined at Block 310 that the strength of the pattern issufficiently high to request an audit, indicating a high level ofnoncompliance, the system 10 may request that the beneficiary be audited(Block 312). Alternatively, if the strength of the pattern is notsufficiently high to request an audit, indicating a low level ofnoncompliance, the system 10 may determine whether the strength of thepattern is high enough to require any number of intermediate actions.

To determine whether an intermediate level has been reached, the system10 may include one or more audit thresholds. An audit threshold mayrelate to the strength of a pattern required for the system 10 torecommend an action. An audit threshold may be predetermined,dynamically variable, or otherwise adjustable. For exemplary purposesonly, this audit threshold may differ for every agency or organizationthat is responsible for distributing the benefit. For example, modestearnings may be allowed under some benefits relating to unemploymentclaims program without impacting the benefits of the claimant. This mayalso be true for beneficiaries that may be receiving disabilitybenefits. But those beneficiaries that may be receiving SupplementalSecurity Insurance payments, for example, may experience an almostimmediate reduction in their benefits. Such a reduction may, forexample, equate to approximately 50 cents for every dollar earned.

Those skilled in the art will appreciate that use of this system mayinclude a refinement period. An algorithm may be run repeatedly againsta database of known compliant and non-compliant beneficiaries untilalerts produced by the algorithm, identify the non-compliantbeneficiaries with a high degree of accuracy while minimizing the numberof false positives that may be produced. This may advantageously allowthe system 10 according to an embodiment of the present invention to beadjusted to certain parameters of a particular agency or entity that isresponsible for distributing a benefit, and further advantageouslyallows the system to be readily used with respect to actualbeneficiaries. Additional discussion regarding the machine learningaspect of an embodiment of the present invention is provided below.

As an example of an audit threshold, and presented without limitation, asingle intermediate level of strength may be defined. A person of skillin the art will appreciate that any number of strengths may be definedand associated with a respective audit threshold. If the system 10determines that the strength of a pattern rises above the levelindicated by an audit threshold, it may recommend a different actionthan had the strength of the pattern fallen below the audit threshold.Skilled artisans will appreciate that a strength of a pattern that isdirectly at a audit threshold, for example, not above or below thethreshold, may be defined by the system 10 to perform one or more actionassociate with being above or below the threshold, as the desiredapplication may require.

Included as an example in flowchart 280, upon determining that the levelof noncompliance is within an acceptable level of noncompliance, forexample, the strength of the pattern is insufficient for requesting anaudit, the system 10 may determine whether the strength of the patternis at an intermediate level (Block 316). Examples of actions that may berequested for an intermediate strength of the pattern may includerequesting that a communication be sent to the beneficiary (Block 314).The operation may then determine whether a shutdown command has beenreceived at Block 318.

If the pattern is not indicative of intermediate strength, or anyadditional level of strength between the high level and the minimallevel of strength, the system 10 may proceed to the operation of Block318, wherein it may determine whether a shutdown command has beenreceived. If no shutdown command has been receive, the system 10 mayreturn to the operation of Block 284, wherein it may again determine apre-benefit pattern or baseline. The subsequent operation of Block 284may be performed in regard to the same beneficiary or a new beneficiary.If a shutdown command is received at Block 318, the operation mayterminate at Block 320.

Referring now to flowchart 330 of FIG. 8, an illustrative example of ananalysis operation to determine whether a beneficiary is ineligible toreceive a benefit will now be discussed. More specifically, anillustrative example of an analysis that compares record data relatingto withdraws that occur in the time period prior to receiving a benefit274 to record data that occurs in the time period following receiving abenefit 276 to determine noncompliance with the rules will now bediscussed. Starting at Block 332, the system 10 may determine apre-benefit pattern, or baseline (Block 334). The baseline may bedetermined, for example, by analyzing banking transactions, such aswithdrawals, that may occur prior to the event. A person of skill in theart will appreciate additional analyses that may be used to determine abaseline to be included herein.

Once a baseline has been established at Block 334, the system 10 mayaccess the record data of the beneficiary. Skilled artisans mayappreciate that the record data may additionally be accessed prior toestablishing the baseline in order to access the record data used toestablish the baseline. Additionally, the record data may be accessedsubsequently or periodically to perform the actions of flowchart 330another time.

Once the record data of the beneficiary has been accessed at Block 336,the system 10 may analyze the record (Block 338). The system 10 maydetermine from the analysis whether a withdrawal included in the recordreaches or exceeds a threshold (Block 340). The threshold may bepredetermined, manually adjustable, dynamical adjustable, scaling, orotherwise variable. If the withdrawal being examined does not reach thethreshold, the operation may continue to Block 368, wherein it may bedetermined whether a shutdown command has been received. However, if awithdrawal is detected that may exceed the threshold at Block 340, thesystem 10 may examine the withdrawal in greater detail (Block 344).Withdrawal details may include, but should not be limited to, merchantinformation, ATM locations, transaction time, or other detailsindicative of the transaction.

The system 10 may determine whether the withdrawal details are invalid(Block 344). If it is determined that the withdrawal details are notinvalid at Block 344, the system 10 may next determine whether thewithdrawal is likely for discretionary shopping, or shopping that doesnot relate to food, bills, and other necessities (Block 348). However,if it is determined at Block 344 that the withdrawal details appear tobe invalid, the system 10 may next determine whether the withdrawaldetails are clearly for necessities. A non-limiting example ofwithdrawal details indicative of an expense that is not clearly anecessity may include a large debit charge from the local pub nearclosing time.

If it is determined at Block 346 that the withdrawal is clearly anecessity, the system 10 may perform the operation of Block 356, whereinit may compare the pattern of the withdrawal to the baseline. If it isdetermined at Block 346 that the withdrawal is not clearly necessary atBlock 346, the operation may proceed, to Block 348 wherein it may bedetermined whether the record data includes frequent occurrences ofdiscretionary withdrawals.

If the system 10 determines that the withdrawals are not related to aclear necessity at Block 346, the system 10 may determine whether thewithdrawals are for discretionary shopping (Block 348). A determinationby the system 10 that the beneficiary has not made discretionarywithdrawals may result in the system 10 continuing to Block 350, whereinit may determine whether frequent withdrawals have been made that arenot for clear necessities (Block 354). Alternatively, if the system 10determines that the withdrawals are apparently for discretionaryshopping at Block 348, the system 10 may increase the strength of thepattern (Block 350) before continuing to the operation of Block 354.

If the system 10 determines that pattern of record data is notindicative of frequent occurrences of withdrawals that are not for clearnecessities at Block 354, it may compare the pattern of the deposits tothe baseline (Block 356). The comparison between the pattern and thebaseline may consider the strength of the pattern during the analysis,among other determinations from the analysis. Alternatively, if thesystem 10 determines that frequent withdrawals are made for reasons thatare not clear necessities, at Block 354, the system 10 may decrease thestrength of the pattern (Block 352) before continuing to the operationof Block 356.

After comparing the pattern to the baseline, the system 10 may determinewhether the pattern is indicative of employment (Block 358). Thisdetermination may weigh the strengths of the patterns with the rankingof the rules. If the pattern is not indicative of employment, the system10 may proceed to the operation of Block 368, wherein it may determinewhether a shutdown command has been received. Alternatively, the system10 may generate a recommendation that no action be taken in regard tothe beneficiary, for example, by recommending that the beneficiary notbe audited. However, if the pattern is indicative of employment at Block358, the system 10 may determine the strength of the pattern todetermine whether an audit should be requested (Block 360).

If it is determined at Block 360 that the strength of the pattern issufficiently high to request an audit, indicating a high level ofnoncompliance, the system 10 may request that the beneficiary be audited(Block 362), i.e., the system may initiate a request for an audit to beperformed. The audit may be manually performed or may be automaticallyperformed using the computerized device. The audit is intended toanalyze several items to increase the probability of detecting when abeneficiary has become ineligible to receive the benefits. The audit mayalso trigger a search of various databases to verify the eligibility ofthe beneficiary to receive benefits. For example, the audit may accessemployment records, social security records, disability records, bankingrecords from several different banks, corporate records (to inquireabout corporate formation), court records (to indicate the award of anyjudgment including, but not limited to, alimony, child support, or thedatabase of the government agency, or other agency responsible fordistributing the benefit to see if the beneficiary recently reportedearned income which failed to trigger the termination of their benefits,or any other types of records that may indicate employment or otheralternative means of revenue that may be available to the beneficiary.Alternatively, if the strength of the pattern is not sufficiently highto request an audit, indicating a low level of noncompliance, the system10 may determine whether the strength of the pattern is high enough torequire any number of intermediate actions.

Included as an example in flowchart 330, upon determining that the levelof noncompliance is within an acceptable level of noncompliance, forexample, the strength of the pattern is insufficient for requesting anaudit, the system 10 may determine whether the strength of the patternis at an intermediate level (Block 366). Examples of actions that may berequested for an intermediate strength of the pattern may includerequesting that a communication be sent to the beneficiary (Block 364).The communication may request that the beneficiary provide updatedinformation to the agency so that a determination may be made as towhether or not the beneficiary remains eligible to receive a benefit.The operation may then determine whether a shutdown command has beenreceived at Block 368. Again, the operation as described in Block 366directed to determining whether or not the strength is intermediate innature and requesting that a communication be sent to the beneficiary isan optional step.

If the pattern is not indicative of intermediate strength, or anyadditional level of strength between the high level and the minimallevel of strength, the system 10 may proceed to the operation of Block368, wherein it may determine whether a shutdown command has beenreceived. If no shutdown command has been receive, the system 10 mayreturn to the operation of Block 334, wherein it may again determine apre-benefit pattern or baseline. The subsequent operation of Block 334may be performed in regard to the same beneficiary or a new beneficiary.If a shutdown command is received at Block 368, the operation mayterminate at Block 370.

Referring now additionally to flowchart 380 of FIG. 9, and illustrativeexample of a feedback system 10 that may be used to improve the accuracyof future determinations and recommendations will now be discussed. Thefeedback system 10 may include a manner of operations to improve theaccuracy of recommended actions, such as, for example, machine learning.Starting at Block 382, the system 10 may receive feedback from the user,which may be an agency (Block 384). For example, and without limitation,the agency may interact with a user interface to input the results of anaudit that had been recommended by the system 10, indicating whether thebeneficiary that had been indicated by the system as potentiallyineligible to receive a benefit was, in fact, ineligible. Skilledartisans will appreciate the inclusion of feedback relating toadditional recommendations that may be made by the system 10 to bewithin the scope of the present invention.

The system 10 may then analyze the feedback to determine the accuracy ofa prior prediction regarding a record indicative of unemployment (Block386). After the analysis has been completed, the system 10 may determinewhether the recommendation for an action was correct (Block 388). If therecommendation was not correct at Block 388, the system 10 may indicatethe incorrect recommendation in the database 101 (Block 390). Thisindication may decrease the likelihood of the system 10 making a similarsubsequent request for the action (Block 392). For example, if thesystem 10 recommended an audit of a beneficiary due to, for example, anew post-benefit income stream of ACH deposits that occurred at two weekintervals and appear to be paychecks, and feedback from the beneficiarydisclosed that they paychecks are to his spouse who recently started anew job, the system 10 may decrease the likelihood of recommending anaudit for the similar subsequent transactions at least for thatparticular income stream for that particular beneficiary

Additionally, if the recommendation was correct at Block 388, the system10 may indicate the correct recommendation in the database 101 (Block394). This indication may increase the likelihood of the system 10making a similar subsequent request for the action (Block 396). Forexample, if the system 10 recommended an audit of a beneficiary due tolarge deposits made every two weeks from a national retail chain andthere no other account holders are listed on the account, and thebeneficiary is receiving unemployment funds, the system 10 may increasethe likelihood of recommending an audit for the similar subsequenttransactions.

After the system 10 has increased or decreased the likelihood of similarsubsequent requests for an action, at Blocks 392 and 396, respectively,the system 10 may indicate the new likelihood of requesting a subsequentaction in the database 101 (Block 398). The operation may then terminateat Block 400.

Referring now additionally to flowchart 410 of FIG. 10, an additionaloperation for applying the accuracy of prior recommendations to improvethe accuracy of subsequent recommendations will now be discussed. Theaccuracy information may have been determined in flowchart 380, forexample, and without limitation. Starting at Block 412, the system 10may access a database 101 that includes data regarding accuracy of priorrecommended actions (Block 414). The system 10 may next analyze theaccuracy information (Block 416). Additionally, the system 10 maygenerate a proposed request for an action relating to the analysisperformed on the record data of a beneficiary (Block 418). A person ofskill in the art will appreciate that the operations of analyzingaccuracy data and generating a proposed request for an action may occursequentially, simultaneously, or in an alternate order.

The system 10 may compare the proposed request for an action to thepreviously accessed and analyzed accuracy data (Block 420). The system10 may then determine whether the proposed request for an action isconsistent with the accuracy data (Block 422). If the proposed requestfor an action is inconsistent with the accuracy data, such that theproposed request is likely to be inaccurate, the system 10 may vacatethe proposed request (Block 424). The system 10 may return to theoperation of Block 418, wherein it may then generate a new proposedrequest for an action.

Conversely, the system 10 may determine that the proposed request for anaction is likely to be accurate at Block 422. Here, the system 10 maygenerate the request for an action (Block 426). The request may then bedelivered to a user, such as an agency, through a user interface. Theoperation may then terminate at Block 428.

Referring now to flowchart 430 of FIG. 11, an illustrative example ofcalculating savings will now be discussed. More specifically, anillustrative example of calculating savings between providing anddenying benefits to ineligible beneficiary will now be discussed.Additionally, sharing a portion of the savings with a third party willalso be discussed.

Starting at Block 432, the system 10 may analyze the record data of thebeneficiaries (Block 434). After analyzing the record data, the system10 may recommend an action (Block 436). A user, such as an agency, maythen perform the recommended action (Block 438). Once the recommendedaction has been performed, the result of the action may be recorded inthe database 101 (Block 440). The analysis of record data,recommendation of an action, and recordation of a result from performingthe action have been discussed previously in the additional examples ofthis disclosure.

After the result has been recorded at Block 440, the system 10 maydetermine a cost savings from performing the recommended action (Block422). The cost savings may be determined; for example, by finding thedifference between the expense of providing the benefit to an ineligiblebeneficiary and the expense of denying the benefit to the ineligiblebeneficiary. A person of skill in the art will appreciate additionalcalculations that may be performed to calculate the savings realized byperforming a successfully recommended benefit.

The system 10 may next determine a portion of the savings, which may bepaid to a third party (Block 446). The portion of savings paid to thethird party may be included as a fee for using the system 10 disclosedherein. Alternatively, a portion of the savings may be directed to anaccount or department to further increase the operational capacityand/or efficiency of the account or department. The operation may thenterminate at Block 448.

Skilled artisans may additionally appreciate that the calculations ofsavings may be calculated over the record data various beneficiaries.Performance of savings calculations over a plurality of beneficiariesmay allow the system 10 to increase the accuracy of actual savings overa calculating relating to a single beneficiary. A further increasedaccuracy may be realized by including the expense of auditing the recorddata of beneficiaries that are not ineligible to receive the benefit.

A person of skill in the art will appreciate that the preceding examplehas been described with detail in the interest of clearly describing anembodiment of the present invention. Skilled artisans will appreciateadditional embodiments of the present invention, wherein theorganization, interaction, and operation may include differences fromthe aforementioned example yet consistent with the scope and spirit ofthe present invention. As a result, skilled artisans would appreciatesuch differences are should not be excluded from the scope of thepresent invention. Many modifications and other embodiments of thepresent invention will come to the mind of one skilled in the art havingthe benefit of the teachings presented in the foregoing descriptions andthe associated drawings. Therefore, it is understood that the inventionis not to be limited to the specific embodiments disclosed.

That which is claimed is:
 1. A method for determining beneficiaryeligibility, the method comprising: accessing record data from afinancial institution relating to banking transactions of a potentiallyineligible beneficiary; analyzing the record data to determine a patternof the banking transactions for a time period prior to receiving thebenefit being defined as a pre-benefit pattern and for a time periodfollowing receiving the benefit being defined as a post-benefit pattern;identifying deviations between the pre-benefit pattern and thepost-benefit pattern; applying a rule selected from a plurality of rulesstored on a database to the deviations to determine a level ofnoncompliance of each of the deviations with the rule; determining alevel of overall noncompliance of the deviations by analyzing the levelof noncompliance of each of the deviations; determining if the level ofoverall noncompliance is within a range of acceptable noncompliance;wherein each of the rules is assigned a predetermined rank according toits importance in determining overall noncompliance with respect to theother rules of the plurality of rules; wherein compliance with the ruleresults in no action being taken; wherein the level of overallnoncompliance being within the range of acceptable noncompliance resultsin no action being taken; wherein the level of overall noncompliancebeing outside the range of acceptable noncompliance results indetermining if the level of overall noncompliance is above an auditthreshold; wherein the level of overall noncompliance being above theaudit threshold results in auditing the record data relating to thebeneficiary; wherein the level of overall noncompliance being below theaudit threshold results in communicating with the beneficiary; whereinthe request for the action to be taken is provided to a user using auser interface; and wherein accessing the record data, analyzing therecord data, identifying the deviations between the pre-benefit patternand the post-benefit pattern, applying the rule, determining the levelof noncompliance, and determining if the level of noncompliance iswithin the range of acceptable noncompliance are carried out using acomputerized device.
 2. A method according to claim 1 wherein the recorddata includes data relating to a deposit of funds; wherein analyzing therecord data further comprises analyzing the data relating to the depositto indicate the pattern of the banking transactions.
 3. A methodaccording to claim 1 wherein the record data includes data relating to awithdrawal of funds; wherein analyzing the record data further comprisesanalyzing the data relating to the withdrawal to indicate the pattern ofthe banking transactions.
 4. A method according to claim 1 wherein therecord data includes data relating to a deposit of funds and awithdrawal of funds; wherein analyzing the record data further comprisesanalyzing the deposit and withdrawal to indicate the pattern of bankingtransactions.
 5. A method according to claim 1 further comprisingproviding a recommendation that the benefit be provided to thebeneficiary upon determining that the level of noncompliance is withinthe range of acceptable noncompliance.
 6. A method according to claim 1further comprising: defining a savings to include a difference betweenthe benefit provided to the beneficiary prior to the benefit beingdenied and the benefit provided to the beneficiary subsequent to thebenefit beings being denied; and sharing a portion of the savings with athird party.
 7. A method according to claim 1 wherein the computerizeddevice includes a network interface that connects to a network; andwherein analyzing the record data to determine the pattern of thebanking transactions further comprises communicating with a bankingcomputerized device through the network.
 8. A method according to claim1 wherein the computerized device includes a network interface thatconnects to a network; and wherein analyzing the record data todetermine the pattern of the banking transactions further comprisescommunicating with a record custodian computerized device through thenetwork and accessing a status record indicative of ineligibility toreceive the benefit from the record custodian computerized device, thestatus record including evidence of the level of noncompliance with therules.
 9. A method according to claim 1 wherein determining whether thelevel of noncompliance with the rules is within the range of acceptablenoncompliance further includes machine learning, the machine learningcomprising: receiving feedback relating to an accuracy of thedetermination of ineligibility of the beneficiary, the feedback beingindicative of the accuracy of an identification of a prior patternindicative of ineligibility of the beneficiary to receive the benefit;accessing the feedback prior to generating a subsequent request for theaction; analyzing the feedback to improve the accuracy of the subsequentrequest for the action.
 10. A method for determining beneficiaryeligibility, the method comprising: accessing record data from afinancial institution relating to banking transactions of a potentiallyineligible beneficiary; analyzing the record data to determine a patternof the banking transactions; applying a rule selected from a pluralityof rules stored on a database to the pattern; determining a level ofoverall noncompliance of the pattern by analyzing the level ofnoncompliance of each of the banking transactions; determining if thelevel of overall noncompliance is within a range of acceptablenoncompliance; wherein compliance with the rule results in no actionbeing taken; wherein the level of overall noncompliance being within therange of acceptable noncompliance results in no action being taken;wherein the level of overall noncompliance being outside the range ofacceptable noncompliance results in determining if the level of overallnoncompliance is above an audit threshold; wherein the level of overallnoncompliance being above the audit threshold results in auditing therecord data relating to the beneficiary; wherein the level of overallnoncompliance being below the audit threshold results in communicatingwith the beneficiary; wherein the request for the action to be taken isprovided to a user using a user interface; wherein each of the rules isassigned a predetermined rank according to its importance in determiningoverall noncompliance with respect to the other rules of the pluralityof rules; wherein accessing the record data, analyzing the record data,applying the rule, determining the level of noncompliance, anddetermining if the level of overall noncompliance is within the range ofacceptable noncompliance are carried out using a computerized device;wherein the computerized device includes a network interface thatconnects to a network; wherein analyzing the record data to determinethe pattern of the banking transactions further comprises communicatingwith a banking computerized device through the network.
 11. A methodaccording to claim 10 wherein the record data includes data relating toat least one of a deposit and a withdrawal of funds; wherein analyzingthe record data further comprises analyzing the data relating to atleast one of the deposits and the withdrawal to indicate the pattern ofthe banking transactions.
 12. A method according to claim 10 furthercomprising: defining a savings to include a difference between thebenefit provided to the beneficiary prior to the benefits being deniedand the benefit provided to the beneficiary subsequent to the benefitbeings being denied; and sharing a portion of the savings with a thirdparty.
 13. A method according to claim 10 wherein determining whetherthe level of noncompliance with the rules is within the range ofacceptable noncompliance further includes machine learning, the machinelearning comprising: receiving feedback relating to an accuracy of thedetermination of ineligibility of the beneficiary, the feedback beingindicative of the accuracy of an identification of a prior patternindicative of ineligibility of the beneficiary to receive the benefit;accessing the feedback prior to generating a subsequent request for theaction; analyzing the feedback to improve the accuracy of the subsequentrequest for the action.
 14. A method according to claim 10 whereinanalyzing the record data to determine the pattern of bankingtransactions further comprises communicating with a record custodiancomputerized device through the network and accessing a status recordindicative of ineligibility to receive the benefit from the recordcustodian computerized device, the status record including evidence ofthe level of noncompliance with the rules.
 15. A system for determiningbeneficiary eligibility, the system comprising: a network interface on acomputerized device that connects to a network, the computerized deviceincluding a memory and a processor; a banking computerized device incommunication with the network; and wherein record data from a financialinstitution relating to banking transactions of a potentially ineligiblebeneficiary is accessed using the computerized device; wherein therecord data is analyzed using the computerized device to determine apattern of the banking transactions; wherein a rule selected from aplurality of rules stored on a database is applied to the pattern of thebanking transactions using the computerized device; wherein a level ofoverall noncompliance of the pattern is determined using thecomputerized device by analyzing the level of noncompliance of each ofthe banking transactions; wherein the level of overall noncompliance isdetermined to be within a range of acceptable noncompliance using thecomputerized device; wherein compliance with the rule results in noaction being taken; wherein the level of overall noncompliance beingwithin the range of acceptable noncompliance results in no action beingtaken; wherein the level of overall noncompliance being outside therange of acceptable noncompliance results in determining if the level ofoverall noncompliance is above an audit threshold by the computerizeddevice; wherein the level of overall noncompliance being above the auditthreshold results in auditing the record data relating to thebeneficiary; wherein the level of overall noncompliance being below theaudit threshold results in communicating with the beneficiary; whereineach of the rules is assigned a predetermined rank according to itsimportance in determining overall noncompliance with respect to theother rules of the plurality of rules; and wherein the request for theaction to be taken is provided to a user using a user interface.
 16. Asystem according to claim 15 wherein the record data includes datarelating to at least one of a deposit and a withdrawal of funds; whereinthe record data that is analyzed includes an analysis of the datarelating to at least one of the deposit and the withdrawal to indicatethe pattern of banking transactions.
 17. A system according to claim 15wherein a savings is defined to include a difference between the benefitprovided to the beneficiary prior to the benefits being denied and thebenefit provided to the beneficiary subsequent to the benefit beingsbeing denied; and wherein a portion of the savings are shared with athird party.
 18. A system according to claim 15 wherein feedbackrelating to an accuracy of the determination of ineligibility of thebeneficiary is received by the computerized device, the feedback beingindicative of the accuracy of an identification of a prior patternindicative of ineligibility of the beneficiary to receive the benefit;wherein the feedback is accessed prior to generating a subsequentrequest for action; and wherein the feedback is analyzed to improve theaccuracy of the subsequent request for action.
 19. A system according toclaim 15 further comprising a records custodian computerized device incommunication with the network; wherein a status record stored on therecord custodian computerized device that is indicative of ineligibilityto receive the benefit is accessed through the network; and wherein thestatus record includes evidence of the level of noncompliance with therules.